Evidence map›Paper›PMID 20890131›Full record

ArticleEpigenetics2011

Global methylation profiles in DNA from different blood cell types.

Hui-Chen Wu, Lissette Delgado-Cruzata, Julie D Flom, Maya Kappil, Jennifer S Ferris, Yuyan Liao, Regina M Santella, Mary Beth Terry

Open access · bronzeAbstract read
In one paragraph

Article in Epigenetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 3 pooled it
9.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

84 citing papers in PubMed, 3 syntheses or guidelines pooled it, 132 citations in OpenAlex.

  1. Pooled it
  2. Epigenetics and human obesity.International journal of obesity (2005) · 2015
    Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Methods in DNA methylation array dataset analysis: A review.Computational and structural biotechnology journal · 2024
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Genome-Wide DNA Methylation Profiles in Community Members Exposed to the World Trade Center Disaster.International journal of environmental research and public health · 2020
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

24 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Hui-Chen WuDepartment of Epidemiology, Mailman School of Public Health of Columbia University, New York, NY, USA.
Lissette Delgado-Cruzata
Julie D Flom
Maya Kappil
Jennifer S Ferris
Yuyan Liao
Regina M Santella
Mary Beth Terry
Columbia University · USNew York Proton Center · US

Funding

Tumor Biology and Microenvironment ProgramP30CA013696 · NCI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI JOSEPH G JURCIC · 1985 to 2026
$115.3M
True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Ami R Zota · 1998 to 2026
$44.7M
METROPOLITAN NEW YORK REGISTRY OF BREAST CANCER FAMILIESU01CA069398 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI TERRY, MARY BETH · 1995 to 2010
$10.5M
NCI NIH HHS CA-06-503NCI NIH HHS P30 CA013696NCI NIH HHS P30 CA13696NCI NIH HHS U01 CA069398NCI NIH HHS U01 CA69398NIEHS NIH HHS P30 ES009089
6 · The paper itself

Abstract

DNA methylation measured in white blood cell DNA is increasingly being used as in studies of cancer susceptibility. However, little is known about the correlation between different assays to measure global methylation and whether the source of DNA matters when examining methylation profiles in different blood cell types. Using information from 620 women, 217 and 403 women with DNA available from granulocytes (Gran), and total white blood cells (WBC), respectively, and 48 women with DNA available from four different sources (WBC, Gran, mononuclear (MN), and lymphoblastoid cell lines (LCL)), we compared DNA methylation for three repetitive elements (LINE1, Sat2, Alu) by MethyLight, luminometric methylation assay (LUMA), and [(3)H]-methyl acceptance assay. For four of the five assays, DNA methylation levels measured in Gran were not correlated with methylation in LBC, MN, or WBC; the exception was Sat2. DNA methylation in LCL was correlated with methylation in MN and WBC for the [(3)H]-methyl acceptance, LINE1, and Alu assays. Methylation in MN was correlated with methylation in WBC for the [(3)H]-methyl acceptance and LUMA assays. When we compared the five assays to each other by source of DNA, we observed statistically significant positive correlations ranging from 0.3-0.7 for each cell type with one exception (Sat2 and Alu in MN). Among the 620 women stratified by DNA source, correlations among assays were highest for the three repetitive elements (range 0.39-0.64). Results from the LUMA assay were modestly correlated with LINE1 (0.18-0.20). These results suggest that both assay and source of DNA are critical components in the interpretation of global DNA methylation patterns from WBC.

Indexed as

Cell LineDNA MethylationFemaleHumansLeukocytesMaleMiddle AgedRepetitive Sequences, Nucleic Acid

Identifiers

PMID20890131
PMCPMC3052916
OpenAlexW2052355316

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.